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Facioscapulohumeral muscular dystrophy type 1 (FSHD1) and Becker muscular dystrophy (BMD) are distinct disorders caused by different genetic variations and exhibiting different inheritance patterns. The co-occurrence of both conditions within the same family is rare. In this case report, the proband was a 10 year-old boy who presented with eye and mouth orbicular muscles, shoulder and proximal upper and lower limbs weakness. Genetic testing showed that the number of D4Z4 repeat units in the sub-terminal region 4qA of chromosome 4q35 in the proband was only 4 (normal value ≥ 11) and, at the same time, a heterozygous deletion was found in exons 13–29 of DMD gene in the proband, thus the diagnosis was clinically and genetically compatible with both FSHD1 and BMD. Pedigree investigation revealed that his maternal grandmother, mother, aunt and cousin also had muscle weakness in the face, shoulders and limbs. Genetic testing confirmed that each of the four relatives had four D4Z4 repeats in the 4qA region, and all of them carried a heterozygous deletion in exons 13–29 of DMD. Based on the X-linked features of DMD/BMD, the maternal grandmother, mother, and aunt were diagnosed with FSHD1 combined with DMD deletion carriers, and the male cousin was diagnosed with FSHD1 combined with BMD. This study identifies a family with a co-occurrence of clinically overt FSHD1 and BMD, which has important reference value for the diagnosis and treatment of hereditary myopathies. [ABSTRACT FROM AUTHOR]

Purpose: The relationship between serum albumin levels and severe limitations in ADLs among stroke patients remains unclear. Specifically, the dose–response relationship between the two needs further exploration. This study aims to provide further results. Materials and methods: This study examined cross-sectional data from patients aged 18 years or older with a diagnosis of stroke confirmed by cranial CT or MRI within 24 h of admission, gathered from January 2020 to August 2022. Data included serum albumin levels, Barthel Index scores recorded after admission, and other essential variables. Results: The study comprised 2,393 stroke patients. After adjusting for confounding factors, the multivariate analysis revealed a 7% decrease in severe impairment of ADL after stroke for every unit (g/L) increase in serum albumin levels. Compared with individuals with lower serum albumin levels (Q1: ≤ 37.4 g/L), the adjusted odds ratios (OR) for severe of ADL impairment among stroke patients in Q2 (37.4–40.21 g/L), Q3 (40.21–42.80 g/L), and Q4 (≥42.8 g/L) were 0.68 (95% CI: 0.4–1.15, p = 0.148), 0.55 (95% CI: 0.32–0.97, p = 0.04), and 0.64 (95% CI: 0.37–1.15, p = 0.139), respectively. The relationship between serum albumin and severe impairment of ADLs in stroke patients showed an L-shaped curve (non-linear, p = 0.002), with an inflection point at 38.0 g/L. The OR for significant impairment of ADLs was 0.680 (95% CI: 0.568–0.814, p < 0.001) in participants with serum albumin levels <38.0 g/L. However, when serum albumin levels were greater than or equal to 38.0 g/L, the severe impairment of ADLs no longer decreased with rising serum albumin levels. Conclusion: In summary, an L-shaped connection with an approximate inflection point of 38.0 g/L was found between blood albumin levels and significant ADL impairment in stroke patients. The results of this study suggest that increasing serum albumin levels can significantly help improve the severity of ADL impairment in stroke patients, particularly those with serum albumin levels below 38.0 g/L. [ABSTRACT FROM AUTHOR]

This paper proposes a method to compute solutions of optimal controls for dynamic systems in terms of radial basis function neural networks (RBFNN) with Gaussian neurons. The RBFNN is used to compute the value function from Hamilton–Jacobi–Bellman equation with the policy iteration. The concept of dominant system is introduced to create initial coefficients of the neural networks to stabilise unstable systems and guarantee the convergence of policy iteration. Model reduction and transfer learning techniques are introduced to improve robustness of RBFNN optimal control, and reduce computational time. Numerical and experimental results show that the resulting optimal control has excellent control performance in stabilisation and trajectory tracking, and much-improved robustness to disturbances and model uncertainties even when the system responses move to a domain of the state space that is larger than the domain where the neural networks are trained. [ABSTRACT FROM AUTHOR]

Purpose: Individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), can experience ongoing, often debilitating symptoms after the acute infection known as Long COVID (LC). LC has profound medical, social, and economic consequences worldwide. Prevalence estimates vary, but it is estimated that 10% to 35% of people infected with SARS-CoV-2 develop LC. The World Health Organization endorses physiotherapy as a vital component in LC symptom management and stabilization. Cardiorespiratory physiotherapists are often involved in the management of patients with LC phenotypes such as post-exertional malaise/post-exertional symptom exacerbation, post-COVID interstitial lung disease, dysautonomia, breathing pattern disorders, and chronic cough. However, specific guidance is lacking regarding physiotherapy assessment and safe intervention strategies. In this review, we describe the relevant pathophysiology of the condition, report common clinical phenotypes, and propose a clinical framework for physiotherapy assessment and safe intervention strategies. [ABSTRACT FROM AUTHOR]